Articles | Volume 17, issue 15
https://doi.org/10.5194/gmd-17-5779-2024
https://doi.org/10.5194/gmd-17-5779-2024
Methods for assessment of models
 | 
01 Aug 2024
Methods for assessment of models |  | 01 Aug 2024

Exploring the potential of history matching for land surface model calibration

Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin

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Cited articles

Andrianakis, I., Vernon, I. R., McCreesh, N., McKinley, T. J., Oakley, J. E., Nsubuga, R. N., Goldstein, M., and White, R. G.: Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda, PLoS Comput. Biol., 11, e1003968, https://doi.org/10.1371/journal.pcbi.1003968, 2015. a
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Beylat, S. and Raoult, N.: simonbeylat/History_Matching_ORCHIDEE: v1.0.0 (Exp_Pot_HM), Zenodo [code, data set], https://doi.org/10.5281/zenodo.10592299, 2024. a
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Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
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